Thank you Ronan (and Nick) for pointing me to some useful software.
And Jean-Benoit for writing it.
I agree about -clv- . It identified a single factor as the best
representation, but also suggested a possible second
factor, based on two scales with a higher than average
correlation. All with the simplest possible format.
BW
Paul Seed
Ronan Conroy <rconroy@rcsi.ie> wrote:
Date Thu, 17 Nov 2011 10:48:26 +0000
>>On 2011 Samh 16, at 18:15, Cameron McIntosh wrote:
>> Hayton, J.C., Allen, D.G., & Scarpello, V. (2004). Factor Retention Decisions in Exploratory Factor Analysis: a Tutorial on Parallel Analysis. Organizational >>Research Methods, 7(2), 191-205.http://orm.sagepub.com/content/7/2/191.full.pdf+html
>A very well worthwhile article. The authors make the point that "Specifying too few factors results in the loss of important information by ignoring a factor or >combining it with another (Zwick & Velicer, 1986). This can result in measured variables that actually load on factors not included in the model, falsely loading >on the factors that are included, and distorted loadings for measured variables that do load on included factors. Furthermore, these errors can obscure the true >factor structure and result in complex solutions that are difficult to interpret (Fabrigar et al., 1999; Wood, Tataryn, & Gorsuch, 1996)."
>
>I really like Jean-Benoit Hardouin's -clv- command in this context, giving a splendid visual display of the structure of the items. It has revealed important >features of data, such as factors-within-factors, that would have been far harder to spot in the output of any factor analytic command.
Ronán Conroy
rconroy@rcsi.ie
Associate Professor
Division of Population Health Sciences
Royal College of Surgeons in Ireland
Beaux Lane House
Dublin 2
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